Battery charge state estimate for a robotic forklift routing system

Abstract

In the context of robotic forklift, battery management is essential and may be considered a key issue in the logistic system management for intelligent warehouses, where goods must be delivered on time according to the monitoring battery State of Charge (SOC) applied to routing system is a tendency to be considered in the planning of warehouses. Based on this scenario, this paper describes a method based on the use of Extended Kalman Filter (EKF), which uses the cell combined model to estimate the battery SOC. Tests were performed to evaluate the estimated battery consumption considering Open Voltage Circuit (OCV) and SOC EKF method applied in a mini robotic forklift. It was possible to verify the battery consumption needed to execute a determined task path and assign a route for the robotic forklift considering the actual SOC.